设为首页 |  加入收藏
首页首页 期刊简介 消息通知 编委会 电子期刊 投稿须知 广告合作 联系我们
一种基于热层析的良恶性乳腺肿瘤分析方法

An analytical method of benign and malignant breast tumors based on thermal tomography

作者: 张子昭  梁成文  李凯扬 
单位: 武汉大学物理科学与技术学院(武汉 430072) 武汉昊博科技有限公司(武汉 430070)
关键词: 热层析;  红外热像图;  肿瘤建模;  肿瘤分析;  乳腺癌 
分类号:R318
出版年·卷·期(页码):2020·39·4(337-343)
摘要:

目的 乳腺肿瘤的早发现一直都是治疗的关键。当人体发生病变时,功能性改变(如温度?新陈代谢等)往往会早于形态学改变。 但大多数乳腺成像手段(如 X 线、超声等)只能在乳腺组织产生变化后确定病变,主要用于临床诊断和术后分析而缺乏对乳腺肿瘤的早期分析。因此,提出了一种基于热层析的简单快捷且无侵入性的乳腺肿瘤分析方法。 方法 通过红外热像仪提取生物体体表温度后,利用 Pennes 方程对生物体三维温度场进行反演从而得到生物体内热源的信息;将肿瘤看作是一个复杂热源,用 MATLAB 建立它的模型, 并在该模型基础上提出一种区分良恶性肿瘤的方法。该模型可测出肿瘤的深度与大小,分别对应肿瘤的解剖位置和新陈代谢状态,并分别分析 280 例和 80 例数据来验证该模型及方法的有效性和准确性。结果 MATLAB 中模型的相关系数 R2大多在 0以上,用 SPSS 26对该区分方法做了 Kappa 分析和卡方分析,Kappa = 0.9,P<0.01。 结论 模型对肿瘤的预测良好,且在此基础上提出的区分良恶性肿瘤方法具有统计学意义。

Objective Early detection of breast tumors has always been the key to treatment. When a disease occurs in the human body, functional changes ( such as temperature, metabolism, etc.) tend to be much earlier than morphological changes. Because most of mammography methods that can only identify the lesions after the changes of breast tissue are mainly used for clinical diagnosis and postoperative analysis, lack early analysis of breast tumors, a new method based on thermal tomography is proposed, which is simple, fast and non-invasive. Methods After extracting the living body's surface temperature with an infrared thermal imager,the method uses the Pennes equation to invert the three-dimensional temperature field of the organism and then the heat intensity of the internal heat source is detected. The tumor is regarded as a complex heat source established by MATLAB, a method to distinguish benign and malignant breast tumors. The model can measure the depth and size of the tumor . The depth corresponds to the anatomical position of the tumor,and the intensity reflects its metabolic state. The effectiveness and accuracy of the proposed model and method is verified by analyzing the data of 280 cases and 80 cases respectively. Results The model’ s R2 is more than 0.9 in most cases. The Kappa analysis result of this method is that Kappa is equal to 0.9,the result of the chi-square is that P is less than 0.01. Conclusions The model predicts tumors well, and the method of distinguishing benign and malignant tumors proposed on this basis has statistical significance.

参考文献:

[ 1 ] Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018:GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[ J]. CA: A Cancer Journal for Clinicians, 2018, 68(6):394-424.

[ 2 ] 沈艳,郭筱兰.早期乳腺癌的影像学筛查现状与进展[ J].中华乳腺病杂志(电子版),2017,11(2):114-116.

[ 3 ] 郑荣寿, 孙可欣, 张思维,等. 2015 年中国恶性肿瘤流行情况分析[J]. 中华肿瘤杂志, 2019, 41(1):19-28.

[ 4 ] 郑莹, 张敏璐. 中西乳腺癌流行差异及其对防治的启示[ J].中华外科杂志, 2015, 53(12):905-909.

[ 5 ] Prieto J, Melero I, Sangro B. Immunological landscape and immunotherapy of hepatocellular carcinoma[ J]. Nature reviews. Gastroenterology and Hepatology, 2015,12(12):681-700.

[ 6 ] Lashkari AE, Pak F, Firouzmand M. Full intelligent cancer classification of thermal breast images to assist physician in clinical diagnostic applications [ J]. Journal of Medical Signals and Sensors, 2016, 6(1):12-24.

[ 7 ] 彭玉兰,黄娟,苏鸣岗.功能影像学技术对乳腺癌诊断的价值[J].中华医学超声杂志(电子版),2015,12(11):823-827.

[ 8 ] Gao CF, Li KY, Zhang SP. A novel approach of analyzing the relation between the inner heat source and the surface temperature distribution in thermal texture maps [ C ] / / International Conference of the IEEE Engineering in Medicine and Biology Society. Shanghai, China:IEEE Press, 2005, 2006:623-626.

[ 9 ] Zhang H, Li KY, Sun SR, et al. The value?exploration of theclinical breast diagnosis by using thermal tomography [ C ] / /Fourth International Conference on Natural Computation. Jinan,China:IEEE Computer Society, 2008:138-142.

[10] Han F, Shi G, Liang C, et al. A simple and efficient method forbreast cancer diagnosis based on infrared thermal imaging [ J].Cell Biochemistry and Biophysics, 2015, 71:491-498.

[11] Han F, Liang CW, . Shi GL, et al. Clinical applications ofinternal heat source analysis for breast cancer identification[ J].Genetics and Molecular Research, 2015, 14 (1):1450-1460.

[12] 乔雨婷, 韩飞, 李文科,等. 曲面拟合技术在医学热层析方法中的应用[ J].计算机应用与软件, 2013,30( 2):231 - 234,258.

Qiao YT, Han F, Li WL, et al. Applying surface fitting inmedical thermal tomography technology [ J ]. ComputerApplications and Software, 2013,30(2):231-234, 258.

[13] 李凯扬,李娟娟,张园园. 热层析技术在致密性乳腺癌新辅助化疗疗效中的应用[C] / / 全国第十七届红外加热暨红外医学发展研讨会论文及论文摘要集.青岛:全国第十七届红外加热暨红外医学发展研讨会,2019:20-24.

[14] 李凯扬,梁成文,史贵连,等. 热层析成像技术及应用[ C] / /全国第十五届红外加热暨红外医学发展研讨会论文及论文摘要集.福州:全国第十五届红外加热暨红外医学发展研讨会, 2015:69-78.

[15] 余玥, 张晓琨. 人工智能技术在乳腺癌诊疗领域的应用[ J].心血管外科杂志(电子版), 2018, 7(1):193-194.

[16] 刘宏岩. 基于人体红外图像的体内热分析建模方法研究[D].中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2018.

[17] Shi GL, Han F, Wang L, et al. Q-r curve of thermal tomography and its clinical application on breast tumor diagnosis [ J ]. Biomedical Optics Express, 2015, 6(4):1109-1123.

[18] Wu Q, Li J, Sun S, et al. Thermal tomography for monitoring tumor response to neoadjuvant chemotherapy in women with locally advanced breast cancer[ J]. Oncotarget, 2017, 8( 40):68974-68983.

服务与反馈:
文章下载】【加入收藏
提示:您还未登录,请登录!点此登录
 
友情链接  
地址:北京安定门外安贞医院内北京生物医学工程编辑部
电话:010-64456508  传真:010-64456661
电子邮箱:llbl910219@126.com